Eindhoven University of Technology (TU/e) is offering a fully funded PhD position in Multi-Faceted Visual Process Analytics within the Department of Mathematics and Computer Science. The research focuses on developing advanced Visual Analytics techniques for event sequence exploration and analysis, bridging the fields of Process Mining and Visualization. The project aims to create a unified framework that leverages dynamic, interactive visual tools to make complex process data accessible and actionable, moving beyond traditional static representations. The successful candidate will work within the award-winning Visualization cluster at TU/e, supervised by Stef van den Elzen and Fernando Paulovich, both recognized experts in the field. The cluster has a strong track record in high-dimensional data visualization and has contributed to major conferences and industry applications. Applicants should hold a Master's degree in Computer Science, Mathematics, or Electrical Engineering, and possess strong programming skills in languages such as Qt/C++, Java, or Python. Experience in Process Mining or Event Visualization is advantageous but not mandatory. The position offers a competitive salary (€3,059–€3,881 per month), a comprehensive benefits package including bonuses, pension, paid leave, and tax advantages for internationals, as well as access to excellent training and research infrastructure. The PhD contract is for four years, with a teaching component and opportunities for professional development. Applications must be submitted online via the TU/e portal, including a cover letter, CV with publications, and contact details for three references. The deadline is December 3, 2025, but applications are reviewed on a rolling basis until the position is filled. For more information, candidates can contact the supervisor or HR services. TU/e is an internationally top-ranking university known for its collaborative and innovative research environment.

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Eindhoven University of Technology, a leading research institution in the Netherlands, is offering six PhD positions focused on advancing design automation and diagnostics in the semiconductor industry. The university is renowned for its collaborative culture and strong ties to high-tech industries, particularly in the Brainport region. These positions span the departments of Mechanical Engineering, Electrical Engineering, and Mathematics and Computer Science, and are aimed at solving complex, multidisciplinary challenges in system-level modelling, analysis, design, and synthesis for semiconductor equipment, especially lithography machines. The research topics include automated computational design synthesis of system topologies, scenario-based system-level performance engineering, timing-aware distributed supervisory controller synthesis, AI-driven legacy system explanation and refactoring, data mining for diagnostics using knowledge graphs and foundation models, and automating health monitoring in semiconductor equipment. Each project is supervised by leading academics and involves collaboration with industry partners such as ASML AI Research. Candidates will work in a vibrant, interdisciplinary environment, receive comprehensive training, and benefit from excellent employment conditions including a four-year contract, competitive salary, bonuses, pension, paid leave, and support for international staff. Applicants must have a master’s degree in a relevant field and demonstrate strong analytical, problem-solving, and teamwork skills. Specific expertise in software engineering, programming, cyber-physical systems, formal methods, AI, data mining, control theory, and related areas is required for certain positions. Applications are accepted online until November 30, 2025, and should include a cover letter, CV, and references. The university provides a supportive infrastructure, professional development opportunities, and a dynamic campus environment. For more information, candidates are encouraged to contact the listed supervisors or HR services.

Eindhoven University of Technology is offering six PhD positions focused on advancing design automation, diagnostics, and AI applications for complex semiconductor systems, particularly lithography machines. These positions span the departments of Mechanical Engineering, Electrical Engineering, and Mathematics and Computer Science, and are designed to address the limitations of current domain-specific automation solutions by developing holistic, system-level approaches. The research topics include automated computational design synthesis of system topologies, scenario-based compositional system-level performance engineering, timing-aware distributed supervisory controller synthesis, AI-driven legacy system explanation and refactoring, data mining for diagnostics using knowledge graphs and foundation models, and automating health monitoring in semiconductor equipment. Each project is supervised by leading academics and, in some cases, involves collaboration with industrial partners such as ASML AI Research. Candidates will work on cutting-edge challenges such as system architecture exploration, model-based performance engineering, supervisory control synthesis, generative AI for software maintenance, advanced diagnostic frameworks, and predictive monitoring technologies. Applicants should have strong backgrounds in relevant fields, with specific skills required for each position, such as software engineering, formal methods, control theory, and AI. The positions offer the opportunity to contribute to innovation in the Brainport region and beyond, working in interdisciplinary teams and with internationally recognized industrial partners. Funding details are not specified in the announcement. Interested candidates should apply online via the AcademicTransfer link, submitting their CV, motivation letter, and transcripts, and indicating their preferred PhD project(s).

This PhD position at Eindhoven University of Technology (TU/e) focuses on developing advanced Visual Analytics techniques for event sequence exploration and analysis, with the goal of enabling Multi-Faceted Visual Process Analytics. The project is situated within the Department of Mathematics and Computer Science, the largest department at TU/e, and is part of the renowned Visualization cluster, which has a strong track record in high-dimensional data visualization and visual analytics. The research aims to bridge the gap between process mining—a computational approach to discovering, analyzing, and optimizing business processes from event logs—and visual analytics, which emphasizes intuitive, interactive exploration of complex, multi-dimensional data. Traditional process mining techniques often focus on control-flow and neglect other important process dimensions such as timing, spatial distribution, and resource relationships. This project seeks to overcome these limitations by integrating dynamic, interactive visual tools that make complex process data accessible and interpretable to a broader audience. The successful candidate will work on creating a unified framework that harmonizes process mining and visual analytics, unlocking deeper insights into processes by incorporating temporal, spatial, and relational aspects into visualizations. The project is supervised by dr.ir. Stef van den Elzen (Assistant Professor) and dr. Fernando Paulovich, both of whom are active in the Visualization cluster at TU/e. The cluster is internationally recognized, with award-winning contributions at major conferences and successful industry collaborations. Applicants should have a strong background in Visualization or Visual Analytics, preferably with a master’s degree in Computer Science, (Applied) Mathematics, or Electrical Engineering. Experience in process mining or event visualization is a plus, as are strong programming skills in object-oriented GUI languages such as Qt/C++, Java, or Python. Good communication skills, creativity, analytical thinking, and proficiency in English are required. The position offers a full-time, four-year contract with a competitive salary (scale P: €3,059–€3,881 per month), year-end and vacation bonuses, pension scheme, paid leave, and additional allowances for commuting, home working, and internet costs. International candidates benefit from a tax compensation scheme and support from the university’s Staff Immigration Team. The application process is online only; candidates must submit a cover letter, CV with publications, and contact details for three references. The vacancy remains open until filled, with a formal deadline of December 3, 2025. TU/e provides a dynamic, interdisciplinary, and international research environment, with excellent infrastructure and support for professional development.

This PhD project at Eindhoven University of Technology focuses on developing advanced Visual Analytics techniques for the exploration and analysis of event sequences, with the goal of enabling Multi-Faceted Visual Process Analytics. The research aims to bridge the gap between process mining—a field within business process management that extracts insights from event logs—and visual analytics, which specializes in the interpretation of complex, multi-dimensional data through interactive visualization. Traditional process mining techniques often emphasize control-flow analysis, neglecting other important process dimensions such as timing, spatial distribution, and resource relationships. This project seeks to overcome these limitations by integrating dynamic, interactive visual tools that make complex process data accessible and interpretable to a broader audience. The research will explore the synergy between process mining and visual analytics, developing new frameworks and techniques that incorporate temporal, spatial, and relational aspects of processes. The project is embedded within the Visualization cluster at TU/e, a group with a strong international reputation for high-impact research in visualization and visual analytics, and a history of award-winning contributions and successful technology transfer. Supervision is provided by Dr.ir. Stef van den Elzen and Dr. Fernando Paulovich, both recognized experts in the field. The successful candidate will have the opportunity to contribute to cutting-edge research, collaborate with leading academics, and develop tools that can transform the way complex processes are analyzed and visualized across domains such as business, healthcare, and supply chain management. The application process is managed via Academic Transfer, and interested candidates should follow the provided link for further details and to submit their application.